Operations Research Department Research Articles

Measuring Outcomes and Objectives for ABET Accreditation in a Systems Engineering Undergraduate Program

AbstractBackgroundUndergraduate program accreditation for undergraduate engineering programs is challenging to faculty. Departments are required to accumulate data and then apply measures to both their outcomes and objectives in their program. The Accreditation Board for Engineering and Technology, ABET, is an accreditation organization for college and university programs in applied science, computing, engineering, and technology. The quality of engineering programs has become a fundamental issue in the educational system in the United States. Accreditation confirms that the institution or the program meets minimum quality criteria. ABET has become more important when licensure is required in many states for engineers to practice. According to information provided in ABET website, “Many state board of professional licensure in engineering and surveying require applicants to have graduated from an ABET‐accredited program. In states where non‐ABET graduates are permitted to be licensed, an additional four to eight years of work experience may be required.” (www.abet.org)ABET provides a sets of goals and objectives for accreditation and evaluates and certifies the engineering related education. In order to prepare for an evaluation of their program, the faculty develops a methodology of assessing the performance with respect to outcomes and objectives that are defined in ABET criteria. Each engineering program develops its objectives and performs internal evaluation to meet ABET criteria.Sources in literature describe different approaches and present various tools to design effective processes for evaluating engineering education and to satisfy ABET criteria. Miller and Olds introduce an evaluation matrix which provides performance criteria, implementation strategies, and evaluation methods. (Olds 1998) Owen, Scales, and Leonard explain the importance of creating a database of outcome indicators for engineering programs. There are many other sources in the literature describing different techniques to create surveys for measuring success and providing strategies to integrate assessment and evaluation into engineering education [Owen 1999].Besides the sources in literature, experiences of institutions when they were accredited provide various approaches. The United States Military Academy (USMA) prepared multiple programs for a joint ABET accreditation. They first established the committees for each department and developed cross‐program reviews. The cross‐program review helped them to identify problem areas and make to correction early. By assigning individual faculty members to be responsible for documenting, the outcome monitoring was established [Huggins 2002].The ECE Department at Cal Poly Pomona developed overall objectives to get accredited: Reviewing department goals and objectives, justifying the program if it meets the goals and objectives, justifying the students if they meet the goals and objectives, assessment and improvement of the program, reviewing course outline, and putting the notebooks together. (http://www.csupomona.edu/~ece/eceweb/abet.html)The College of Engineering at The University of Wisconsin Madison outlined four primary activities: Developing department level outcomes, developing course objectives for undergraduate courses, hosting a working conference on ABET preparation, and developing a web‐site for accreditation and assessment (Pfatteicher 2000).At the University of Arizona, the department of Engineering established two teams: ABET implementation team and ABET assessment team. The implementation team consisted of one person from each department to coordinate the activities and assessment team had individuals with specific skills. They created educational objectives and expected outcomes. Expected outcomes later were expressed in terms of measurable activities such as the outcome of working in a multi‐disciplinary team was expressed in terms of completing team lab exercises and completing Engineering 102 projects. They used primary assessment tools such as student, alumni, and faculty surveys and portfolios (Johnson 1999).As can be seen by the various references above, each engineering department may use different processes to achieve the same results, accreditation.The purpose of this paper is to present the process used by the Systems Engineering and Operations Research Department at George Mason University to accredit our Systems Engineering undergraduate program with special emphasis on measurement of outcomes and objectives.

Process for ABET Accreditation in a Systems Engineering Undergraduate Program

AbstractBackgroundAccreditation of engineering undergraduate programs is very important to both the university and the students graduating from the program. The Accreditation Board for Engineering and Technology, ABET, is an accreditation organization for college and university programs in applied science, computing, engineering, and technology. The quality of engineering programs has become a fundamental issue in the educational system in the United States. Accreditation confirms that the institution or the program meets the minimum quality criteria. ABET has become more important when licensure is required in many states for engineers to practice. According to information provided in ABET website, “Many state board of professional licensure in engineering and surveying require applicants to have graduated from an ABET‐accredited program. In states where non‐ABET graduates are permitted to be licensed, an additional four to eight years of work experience may be required.” (www.abet.org) Some of the advantages of accreditation of the program or institutions are as follows: (www.abet.org) Accreditation provides structured method to assess, evaluate, and improve the qualify of the program Accreditation helps students and families choose quality programs Accreditation enables employers to recruit graduates that are well‐prepared Accreditation is used by registration, licensure, and certification boards to screen applicantsFrom the ABET Viewpoints Volume 1, it is pointed out that ABET helps improving Ethics Awareness in higher education [Viewpoints 2005].ABET provides a sets of goals and objectives for accreditation and evaluates and certifies the engineering related education. After requesting an evaluation of its program, the faculty develops a methodology of assessing the performance with respect to outcomes that are defined in ABET criteria. Each engineering program develops its objectives and performs internal evaluation to meet ABET criteria.Sources in literature describe different approaches and present various tools to design effective processes for evaluating engineering education and to satisfy ABET criteria. Miller and Olds introduce an evaluation matrix which provides performance criteria, implementation strategies, and evaluation methods. (Olds 1998) Owen, Scales, and Leonard explain the importance of creating a database of outcome indicators for engineering programs. There are many other sources in the literature describing different techniques to create surveys for measuring success and providing strategies to integrate assessment and evaluation into engineering education [Owen 1999].Besides the sources in literature, experiences of institutions when they were accredited provide various approaches. The United States Military Academy (USMA) prepared multiple programs for a joint ABET accreditation. They first established the committees for each department and developed cross‐program reviews. The cross‐program review helped them to identify problem areas and make to correction early. By assigning individual faculty members to be responsible for documenting, the outcome monitoring was established [Huggins 2002]. The ECE Department at Cal Poly Pomona developed overall objectives to get accredited: Reviewing department goals and objectives, justifying the program if it meets the goals and objectives, justifying the students if they meet the goals and objectives, assessment and improvement of the program, reviewing course outline, and putting the notebooks together. (http://www.csupomona.edu/~ece/eceweb/abet.html)The College of Engineering at The University of Wisconsin Madison outlined four primary activities: Developing department level outcomes, developing course objectives for undergraduate courses, hosting a working conference on ABET preparation, and developing a web‐site for accreditation and assessment (Pfatteicher 2000).At the University of Arizona, the department of Engineering established two teams: ABET implementation team and ABET assessment team. The implementation team consisted of one person from each department to coordinate the activities and assessment team had individuals with specific skills. They created educational objectives and expected outcomes. Expected outcomes later were expressed in terms of measurable activities such as the outcome of working in a multi‐disciplinary team was expressed in terms of completing team lab exercises and completing Engineering 102 projects. They used primary assessment tools such as student, alumni, and faculty surveys and portfolios (Johnson 1999).As can be seen by the various references above, each engineering department may use different processes to achieve the same results, accreditation.The purpose of this paper is to present the process used by the Systems Engineering and Operations Research Department at George Mason University to accredit our Systems Engineering undergraduate program.

Foreword to the Symposium

This collection of papers is dedicated to Mukul Majumdar, in appreciation of his contributions to the economics profession. Mukul Majumdar came to the United States from India in 1965, for graduate study in economics at the University of California, Berkeley. He completed his Ph.D. in 1970 under the supervision of Roy Radner. He joined the faculty of Stanford University in 1969 and after spending a year as a Visiting Lecturer at the London School of Economics (in 1972–1973), he moved to Cornell University, where he has remained since. He was the chairman of the Department of Economics at Cornell University from 1978 to 1983, and was responsible for shaping its graduate program as well as its recruiting of new faculty members during those years. As a graduate student at Berkeley, Mukul Majumdar was greatly influenced by the research of Rabi Bhattacharya and David Blackwell (in the Statistics Department), of Gerard Debreu, Daniel McFadden and Roy Radner (in the Economics Department), and of David Gale (in the Mathematics Department and the Industrial Engineering and Operations Research Department). He learned from his mentors

Timing the smile

Within the general framework of stochastic volatility, the authors propose a method, which is consistent with no-arbitrage, to price complicated path-dependent derivatives using only the information contained in the implied volatility skew. This method exploits the time scale content of volatility to bridge the gap between skews and derivatives prices. Here they present their pricing formulas in terms of Greeks free from the details of the underlying models and mathematical techniques. 1 Underlying or Smile? Our goal is to address the following fundamental question in pricing and hedging derivatives. How traded call options, quoted in terms of implied volatilities, can be used to price and hedge more complicated contracts. One Department of Mathematics, NC State University, Raleigh NC 27695-8205, fouque@math.ncsu.edu. Work partially supported by NSF grant DMS-0071744. Department of Mathematics, Stanford University, Stanford CA 94305, papanico@math.stanford.edu. Department of Operations Research & Financial Engineering, Princeton University, E-Quad, Princeton, NJ 08544, sircar@princeton.edu. Department of Mathematics, University of California, Irvine CA 92697, ksolna@math.uci.edu.

Some Recent Results on The Linear Complementarity Problem

In this article we present some recent results on the linear complementarity problem. It is shown that (i) within the class of column adequate matrices, a matrix is in $\Qnot$ if and only if it is completely $\Qnot$ (ii) for the class of $\Cnotf$-matrices introduced by Murthy and Parthasarathy [SIAM J. Matrix Anal. Appl., 16 (1995), pp. 1268--1286], we provide a sufficient condition under which a matrix is in $\Pnot$ and as a corollary of this result, we give an alternative proof of the result that $\Cnotf \cap \Qnot \sset \Pnot$ (iii) within the class of INS-matrices introduced by Stone [Department of Operations Research, Stanford University, Stanford, CA, 1981], a nondegenerate matrix must necessarily have the block property introduced by Murthy, Parthasarathy, and Sriparna [G. S. R. Murthy, T. Parthasarathy, and B. Sriparna, Linear Algebra Appl., 252 (1997), pp. 323--337]. Furthermore, we conjecture that if a matrix has block property, then it must be Lipschitzian. This problem is an important one from two angles: if the conjecture is true, it provides a finite test to check whether a given matrix is Lipschitzian or nondegenerate INS; and it settles an open problem posed by Stone. It is shown that the conjecture is true in the cases of 2 x 2-matrices, nonnegative and nonpositive matrices of general order.

OPTION PRICING BOUNDS AND THE PRICING OF BOND OPTIONS

Journal of Business Finance & AccountingVolume 23, Issue 4 p. 535-556 OPTION PRICING BOUNDS AND THE PRICING OF BOND OPTIONS Bjarne Astrup Jensen, Bjarne Astrup JensenSearch for more papers by this authorJørgen Aase Nielsen, Corresponding Author Jørgen Aase Nielsen The authors are respectively from the Institute of Finance, Copenhagen Business School; and the Department of Operations Research, Århus University. They wish to thank the anonymous referee for valuable comments on earlier drafts of this paper. Financial support from the Danish Social Science and Danish Natural Science Research Councils during the latter part of the working period of the present research project is gratefully acknowledged.Department of Operations Research, Århus University, Building 530, Ny Munkegade, DK-8000 Århus C., Denmark.Search for more papers by this author Bjarne Astrup Jensen, Bjarne Astrup JensenSearch for more papers by this authorJørgen Aase Nielsen, Corresponding Author Jørgen Aase Nielsen The authors are respectively from the Institute of Finance, Copenhagen Business School; and the Department of Operations Research, Århus University. They wish to thank the anonymous referee for valuable comments on earlier drafts of this paper. Financial support from the Danish Social Science and Danish Natural Science Research Councils during the latter part of the working period of the present research project is gratefully acknowledged.Department of Operations Research, Århus University, Building 530, Ny Munkegade, DK-8000 Århus C., Denmark.Search for more papers by this author First published: June 1996 https://doi.org/10.1111/j.1468-5957.1996.tb01025.xCitations: 1 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume23, Issue4June 1996Pages 535-556 RelatedInformation

What the Government Needs

Click to increase image sizeClick to decrease image sizeKey Words: Applied statistical experienceData qualityPublic policyStatisticianTraining

Reduced System Algorithms for Markov Chains

A reduced system is a smaller system derived in the process of analyzing a larger system. In solving for steady state probabilities of a Markov chain, generally the solution can be found by first solving a reduced system of equations which is obtained by appropriately partitioning the transition probability (or rate) matrix. Following Lal (Lal, R. 1981. A unified study of algorithms for steady state probabilities in Makov chains. Ph.D. Dissertation, Department of Operations Research and Engineering Management, School of Engineering and Applied Sciences, Southern Methodist University, Dallas, TX 75275.), a Markov chain can be categorized as standard or nonstandard depending on the location of an invertible submatrix necessary for an efficient solution in a transition probability (or rate) matrix. In this paper, algorithms for the determination of steady state probabilities are developed by using (i) a backward recursion which is efficient for standard systems and (ii) a forward recursion which is efficient for nonstandard systems. It is also shown that the backward recursion can be used for finding the first passage time distribution and its mean and variance.

Modelling energy consumption in manufacturing industry

The major effort in energy modelling has been directed to national and global consumption. This paper describes how the techniques of multivariate statistical analysis can be used to model energy consumption in a production environment with varying levels of production activity and weather conditions. The author discusses how the methods were applied by the Operational Research Department at Lancaster University to a manufacturing group of six companies involved in making various products for the engineering and construction industry. The paper identifies the practical issues that arose through the project and describes how the energy models are used for budgeting monthly fuel consumption and for evaluating new energt policies.

Operational operations research at the Mathematical Centre

This note deals with consultation in operations research at the Mathematical Centre in Amsterdam. After a short description of the activities of the MC, in particular of its Department of Operations Research and System Theory, three practical projects are described.

Short Term Forecasting: Horses for Courses

Within the British Gas Corporation the Headquarters Operational Research Department has assisted various clients with a range of short term forecasting problems. As a result, over the years considerable experience has been gained with the use of alternative forecasting procedures. The authors felt that it would be interesting to compare the usefulness of these alternative approaches, not as usual by their forecasting performance measured in terms of some statistical parameter, but rather in terms of some qualitative factors. Amongst these we identify the objectives of the forecaster, nature of the environment, ease of use and nature of the time series itself. Such factors we believe may well be more important than the forecasting performance as determined by strictly statistical measures. This paper discusses, in these terms, our experience of using alternative forecasting models for appliance sales and gas sendout forecasting problems.

Algorithm 583: LSQR: Sparse Linear Equations and Least Squares Problems

Received 4 June 1980; revised 23 September 1981, accepted 28 February 1982 This work was supported by Natural Sciences and Engineering Research Council of Canada Grant A8652, by the New Zealand Department of Scientific and Industrial Research; and by U S. National Science Foundation Grants MCS-7926009 and ECS-8012974, the Department of Energy under Contract AM03-76SF00326, PA No. DE-AT03-76ER72018, the Office of Naval Research under Contract N00014-75-C-0267, and the Army Research Office under Contract DAA29-79-C-0U0, Authors' addresses: C. C. Paige, School of Computer Science, McGill University, Montreal, Quebec, Canada H3A 2K6; M. A Saundem, Department of Operations Research, Stanford University, Stanford, CA 94305. Permmsion to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notme is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. © 1982 ACM 0098-3500/82/0600-0[95 $00 75

Letters to the Editor

—To the Editor: Re: Queuing Theory: Two Nations by Ernest Koenigsberg, School of Business Administration, University of California at Berkeley; —To the Editor: Re: “Quickening the Queue in Grocery Stores,” by Jones, O'Berski and Tom, Interfaces June 1980 by Robert G. Chamberlain, Operations Research Group, Jet Propulsion Laboratory, California Institute of Technology; —The Authors' Reply by Michael T. Jones, Arlene M. Oberski, and Gail Tom, School of Business and Public Administration, California State University at Sacramento; —To the Editor: Re: On-line Scheduling by Hodgson, February 1980 issue, p. 77 by Glenn T. Wilson, Management Science Department, Southern Illinois University; —To the Editor: Re: Nahmias, Steven, 1980, “The Use of Management Science to Support a Multimillion Dollar Precedent-Setting Government Contract Litigation,” Interfaces Vol. 10, No. 1, p. 1 by J. W. Hargrove, Jr., Department of Operations Research, Naval Post Graduate School; —The Author Responds by Steven Nahmias, Graduate School of Business, The University of Santa Clara; —To the Editor: Re: Doll, Loren, C., “Quick and Dirty Vehicle Routing Procedure,” Interfaces February, 1980, pp. 84–85 by David Ronen, School of Business Administration, University of Missouri-St. Louis; —Call for Papers: Mathematical Programming With Data Perturbations (Third Symposium on Mathematical Programming with Data Perturbations at The George Washington University, May 21–22, 1981.) by Anthony V. Fiacco, Department of Operations Research, School of Engineering and Applied Science, The George Washington University, Washington, D.C.

After 25 Years: A Survey of Operations Research Alumni, Case Western Reserve University

As the Department of Operations Research at Case Western Reserve University entered its 25th academic year, it became apparent that a survey of past graduates would be valuable in planning for future academic excellence. In view of the fact that this Department is the oldest one of its kind in an academic institution, the significance of such a survey assumed special importance. Consequently, questionnaires were sent to alumni requesting factual and attitudinal responses in such areas as their educational background, curriculum studied, career path followed and utility of the degree. The questionnaire was designed by the authors in consultation with the Department Chairman. Mailings, together with telephone calls, brought 137 responses from the initial list of 221 alumni, or a 62 percent response rate. Of these 137, 81 had received the M.S. in O.R. as their highest degree from the Department, and 56, the Ph.D. degree.

Facilities Expansion Model

The Operations Research Department was requested by the Tubular Products Division to assist in determining the production capabilities for their new facilities. This was a crucial management decision not only because substantial capital had to be committed but the production capability of the new facilities would greatly affect the division's ability to compete in the expanding specialty tubing industry. A linear programming model of the existing and the proposed facilities was developed to evaluate alternative facilities. The forecasted annual shipments for seven major material grades were broken down into six hundred product categories based upon historical size mix patterns. The model assigned these product categories to existing and proposed facilities taking into consideration the operating capabilities, efficiencies, and capacities of the facilities in order to minimize the total operating costs. Eighteen proposed facilities were evaluated under varying market forecasts. In addition, the model was used to evaluate phasing out older facilities, different locations for new facilities, and different startup dates for the new facilities. The production capabilities for the new facility chosen by division management was identified by the model. Division management felt that the new facilities would substantially increase their ability to compete in the specialty tubing industry plus reduce annual operating costs by several million dollars.

Set covering: Uses, algorithms, results : Salkin HM and Saha J (1973) Technical memorandum no. 272, Department of Operations Research, Case Western Reserve University, Cleveland, Ohio 44106, U.S.A.

Set covering: Uses, algorithms, results : Salkin HM and Saha J (1973) Technical memorandum no. 272, Department of Operations Research, Case Western Reserve University, Cleveland, Ohio 44106, U.S.A.

An assessment of the application of on-line computers to control of an underground railway—A simulation study

This paper describes the method and summarizes the results of work within the Operational Research Department of London Transport to assess the benefits that on-line computer control of signals on the Northern and Victoria Lines would bring to passengers. From a simulation study it was concluded that reduction in travel times, waiting times and overcrowding could be achieved by computer control. In the simulation, travel time from Morden to Kings Cross was reduced by 1 min and passenger waiting time at stations reduced by up to 11 sec. The improvement derives mainly from better integration of conflicting movements. The total benefit to passengers over the Northern Line is estimated to be £64,000 p.a. In addition there is the possibility of £13,000 in increased revenue to London Transport from generated traffic.

A task analysis in a clinical specialty providing data for a new curriculum for anesthesia personnel

THE UNITED STATES, in general, and many areas, in particular, face shortages of professionals in the field of health care delivery. Specifically, there exists a shortage of people qualified to administer anesthesia during surgery and obstetrics. Many hospitals do not have a qualified anesthesiologist available. Board certified anesthesiologistst are in short supply nationwide. The problem is further compounded by a geographical maldistribution of these critical skills. About 50 per cent of the anesthetics given in this country are administered by nurses. Nurse anesthetists also are in short supply [43. In order to train additional members of this latter profession, it is necessary to deplete the pool of available trained nurses. A committee of nine anesthesiologists representing major hospitals in the greater Cleveland area have been concerned with the ways and means of responding to the above problems. This group, in cooperation with members of the Department of Operations Research, Case Western Reserve University, addressed the following questions:

Symposium on nonlinear programming at the George Washington University

A Symposium on Nonlinear Programming was held at The George Washington University on 14-16 March 1973. It was sponsored by the Mathematical Programming Society under the auspices of the Office of Naval Research and the university's Department of Operations Research. The conference was organized and conducted by Anthony V. Fiacco (Program Chairman), Garth P. McCormick (Arrangements Chairman) and James E. Falk (Publicity Chairman).

SUBJECTIVE PROBABILITY OF VICTIMIZATION AND CRIME LEVELS: An Econometric Approach

CriminologyVolume 11, Issue 1 p. 87-94 SUBJECTIVE PROBABILITY OF VICTIMIZATION AND CRIME LEVELS: An Econometric Approach M. K. Block, M. K. BlockSearch for more papers by this authorG. J. Long, G. J. LongSearch for more papers by this author M. K. Block, M. K. BlockSearch for more papers by this authorG. J. Long, G. J. LongSearch for more papers by this author First published: May 1973 https://doi.org/10.1111/j.1745-9125.1973.tb00588.xCitations: 16 AUTHOR'S NOTE: Research by M. K. Block was supported by NSF gmnt GS-2942. M. K. BLOCK was Assistant Professor of Economics at the University of Santa Clara and is currently writing his Ph.D. dissertation at Stanford on the economics of theft. He is presently affiliated with the Department of Operations Research and Administrative Sciences at the Naval Postgraduate School in Monterey. G. J. LONG is Assistant Professor of Economics at the University of Santa Clara. He received his Ph.D. from the University of Oregon, after which he taught at Wayne State University before coming to Santa Clara. AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume11, Issue1May 1973Pages 87-94 RelatedInformation